1. Field
One or more embodiments relate to a method of localization and mapping of a mobile robot.
2. Description of the Related Art
Simultaneous localization and mapping (SLAM), a localization and mapping technique of a mobile robot, may be classified into two major categories. The first is recognition of the position of the mobile robot in an environment containing a specific indicator (e.g., a landmark or a beacon) recognizable by the mobile robot. The second is recognition of the position of the mobile robot in a general environment containing no specific indicator. In the case of the second category, various sensors are used to recognize the position in an environment containing no specific indicator. Representative sensing techniques used in this case include techniques of utilizing images, lasers, and ultrasound. These sensing techniques have been conventionally utilized to find landmarks distinct from other positions and discretely create the same to recognize the position of the mobile robot. Recently, research has been conducted into utilization of a continuous vector field, which is an extension of discrete landmarks, to reduce errors in localization and mapping.
However, in the case that a vector field is created using a single sensor to utilize the vector field, movement of the mobile robot around a cell configuring the vector field or along the boundary of the cell may result in insufficient updating of the information about the nodes (the boundary of the cell). Thereby, position errors may not be reduced. Particularly, when the mobile robot moves at a high speed, the errors may be worsened.